Despite its immediate relevance in homeland security applications, high sensitivity detection of explosives using real-time, miniature sensors still remains as a crucial challenge. Although widely used and highly effective, trace explosive detection based on canines is neither cost effective nor suitable for mass deployment. Currently available technologies, such as ion mobility spectrometry and nuclear quadrupole resonance spectroscopy, are bulky and expensive. Optical spectroscopic techniques, such as Raman and laser-induced breakdown spectroscopies, are highly selective but suffer from poor sensitivity. Micro-electro-mechanical systems (MEMS) can potentially satisfy many of the requirements for an ideal compact chemical sensor, such as low-power consumption, real-time operation, and high sensitivity. However, the suitability of MEMS as practical sensors for vapor detection has traditionally been limited by a lack of chemical selectivity.
The selectivity challenge encountered with micromechanical sensors is not unique to MEMS. Other gravimetric sensors such as quartz crystal microbalance (QCM) and surface acoustic wave (SAW) devices, also lack intrinsic selectivity and rely on selective interfaces for chemical speciation. The need for chemical selectivity forces the use of separation techniques or the use of highly selective recognition layers that are irreversible at room temperature. Although attractive from an analytical standpoint, incorporation of separation techniques with MEMS sensors poses integration problems, especially for explosives detection due to the large volumes of air needed for sample collection.
At present there exist no room-temperature reversible receptors that are highly selective for vapor molecules, especially explosive vapors. Designing high specificity molecular recognition layers for small molecules is challenging due to the limited number of chemical interactions that can serve as a basis for designing selective layers while satisfying the highly desirable sensor attribute of room temperature reversibility.
Approaches for achieving selectivity by using sensor arrays modified with partially selective interfaces and pattern recognition work are presently underway. The molecular recognition interfaces based on weak interactions are not specific enough to produce unique responses with a single sensor. Unique responses (orthogonal) cannot be obtained if the mechanism behind individual sensor elements is unspecific, for example, hydrogen bonding of analyte with the chemoselective layer. Increasing the number of sensor elements in the array for pattern recognition analysis can improve the selectivity only if the responses from individual sensing elements are orthogonal. However, there are only a limited number of weak reversible chemical interactions that can serve as a basis for designing the selective layers. Therefore, despite the chemical sensing advantages offered by microfabricated sensors, their use as a practical sensor may be limited without the development of techniques that can generate orthogonal responses.